Mark S. Schmalz

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 1996, OCEANS 96 MTS/IEEE Conference Proceedings. The Coastal Ocean - Prospects for the 21st Century.

Image retrieval using the longest approximate common subsequences

Gerhard X. Ritter, Wen-Chen Hu, Mark S. Schmalz, 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

Region segmentation techniques for object-based image compression: a review

Gerhard X. Ritter, Mark S. Schmalz, G. Ritter, 2004, SPIE Optics + Photonics.

On the convergence of image compression and object recognition

Mark S. Schmalz, 2005, ACM-SE 43.

A Fractal Geometric Model Of Light Pulse Propagation In A Multilayer Ocean

Frank M. Caimi, Mark S. Schmalz, 1986, Other Conferences.

Performance and Energy Evaluation of SAR Reconstruction on Intel Knights Landing

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2018, 2018 Ninth International Green and Sustainable Computing Conference (IGSC).

Analysis and Characterization of Pattern Classifiers; GASP - Generator of Adaptive Statistical Pattern Recognition Systems

Gerhard X. Ritter, Mark S. Schmalz, Gary Key, 2003 .

General theory for the processing of compressed and encrypted imagery with taxonomic analysis

Mark S. Schmalz, 1992, Defense, Security, and Sensing.

Optical and electro-optical architectures for the compression and encryption of discrete signals and imagery: 3. Optical computation over compressed data

Mark S. Schmalz, M. Schmalz, 1994, Defense, Security, and Sensing.

Parallel processing of run-length-encoded Boolean imagery: linear transformations and high-level image operations

Mark S. Schmalz, 1993, Defense, Security, and Sensing.

EBLAST: efficient high-compression image transformation: I. Background and theory

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 1999, Optics + Photonics.

Implementation and Results

Gerhard X. Ritter, Mark S. Schmalz, 2017 .

Automated detection and recognition of small targets in compressed imagery: background and theory

Mark S. Schmalz, 1996, Defense, Security, and Sensing.

Dynamic data driven image reconstruction using multiple GPUs

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2016, 2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

Object-Based Image Compression

Mark S. Schmalz, M. Schmalz, 2003, SPIE Optics + Photonics.

EBLAST: an efficient high-compression image transformation 3. application to Internet image and video transmission

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 2001, SPIE Optics + Photonics.

Introduction to the recognition of patterns in compressed data: 1. image template operations over block-, transform-, runlength-encoded, and vector-quantized data

Mark S. Schmalz, 1995, Defense, Security, and Sensing.

Techniques for region coding in object-based image compression

Mark S. Schmalz, M. Schmalz, 2004, SPIE Optics + Photonics.

Approximating the longest approximate common subsequence problem

Gerhard X. Ritter, Wen-Chen Hu, Mark S. Schmalz, 1998, ACM-SE 36.

COQUINA: content-queryable image and signal archives

Gerhard X. Ritter, Wen-Chen Hu, Mark S. Schmalz, 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

Lattice associative memories that are robust in the presence of noise

Gerhard X. Ritter, Mark S. Schmalz, Gonzalo Urcid-Serrano, 2005, SPIE Optics + Photonics.

NOISE-TOLERANT HYPERSPECTRAL SIGNATURE CLASSIFICATION IN UNRESOLVED OBJECT DETECTION WITH ADAPTIVE TABULAR NEAREST NEIGHBOR ENCODING

Mark S. Schmalz, M. Schmalz, 2008 .

Mathematics of data/image coding, compression, and encryption IV, with applications : 30-31 July, 2001, San Diego, USA

Mark S. Schmalz, 2001 .

Benchmarking techniques for evaluation of compression transform performance in ATR applications

Mark S. Schmalz, M. Schmalz, 2004, SPIE Optics + Photonics.

Nonlinear classification of hyperspectral signatures in high noise

Gerhard X. Ritter, Mark S. Schmalz, Eric T. Hayden, 2013, 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

EBLAST: Efficient high-compression image transformation: II. Implementation and results

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 2000, SPIE Optics + Photonics.

Autonomous single-pass endmember approximation using lattice auto-associative memories

Gerhard X. Ritter, Mark S. Schmalz, Gonzalo Urcid, 2009, Neurocomputing.

Automated analysis and prediction of accuracy and performance in ATR algorithms: II. Experimental results and system performance analysis

Mark S. Schmalz, 1997, Defense, Security, and Sensing.

Massively parallel computation of lattice associative memory classifiers on multicore processors

Gerhard X. Ritter, Mark S. Schmalz, Eric Hayden, 2011, Optical Engineering + Applications.

Learning In Lattice Neural Networks that Employ Dendritic Computing

Gerhard X. Ritter, Mark S. Schmalz, 2006, FUZZ-IEEE.

Front Matter: Volume 7075

Jaakko Astola, Junior Barrera, Gerhard X. Ritter, 2008 .

Parallel processing techniques for the processing of synthetic aperture radar data on GPUs

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2010, 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

Techniques for mapping synthetic aperture radar processing algorithms to multi-GPU clusters

Sartaj Sahni, Guna Seetharaman, Sanjay Ranka, 2012, 2012 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

Performance analysis of tabular nearest-neighbor encoding for joint image compression and ATR: II. Results and analysis

Frank M. Caimi, Mark S. Schmalz, Gary Key, 1999, Optics + Photonics.

Processing of compressed and encrypted imagery: complexity analyses with application to novel regimes of efficient computation

Mark S. Schmalz, 1992, Defense, Security, and Sensing.

Parallel processing of run-length-encoded Boolean imagery: RLE transformation, arithmetic, and global-reduce operations

Mark S. Schmalz, 1993, Defense, Security, and Sensing.

Mathematics of data/image coding, compression, and encryption : 21-22 July 1998, San Diego, California

Mark S. Schmalz, 1998 .

Adaptive wireless thin-client model for mobile computing

Abdelsalam Helal, Mark S. Schmalz, Mohammad Al-Turkistany, 2009, Wirel. Commun. Mob. Comput..

Parallel processing techniques for the processing of synthetic aperture radar data on FPGAs

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2010, The 10th IEEE International Symposium on Signal Processing and Information Technology.

Space, time, error, and power optimization of image compression transforms

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 2000, SPIE Optics + Photonics.

Detection of small targets in compressed imagery: II. Performance of advanced edge detectors, morphological operations, and component labeling over VQ- and VPIC-compressed imagery

Mark S. Schmalz, 1997, Defense, Security, and Sensing.

Model-based landmine detection algorithms for acoustic/seismic data

Paul D. Gader, James M. Keller, Gerhard X. Ritter, 2003, SPIE Defense + Commercial Sensing.

Energy Aware Time Change Detection using Synthetic Aperture Radar on High-Performance Heterogeneous Architectures: A DDDAS Approach

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2020 .

Network Centered Multiple Resource Scheduling in e-Science Applications

Sartaj Sahni, Sanjay Ranka, Yan Li, 2009, GridNets.

Compressive Underwater Video Camera (CUVC)

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 1997 .

On the processing of compressed and encrypted signals and imagery, with applications in efficient, secure computation

Gerhard X. Ritter, Mark S. Schmalz, 1996 .

Advances in predicting spatial deformations in imagery acquired by viewing through the sea surface

Mark S. Schmalz, 1996, Defense, Security, and Sensing.

Compression Transforms: Image Quality Measures

Frank M. Caimi, Mark S. Schmalz, 2015 .

Limits on computational precision of image compression transformations

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 1998, Optics & Photonics.

A SIMD-parallel model of hierarchical, rule-based pattern recognition, with application to the optical interpretation of natural language

Mark S. Schmalz, 1994 .

Spatial exemplars and metrics for characterizing image compression transform error

Frank M. Caimi, Mark S. Schmalz, M. Schmalz, 2001, SPIE Optics + Photonics.

Detection and Characterization of Motion in Video Compression

Gerhard X. Ritter, Mark S. Schmalz, G. Ritter, 2003, SPIE Optics + Photonics.

Optical and electro-optical architectures for the compression and encryption of discrete signals and imagery: 2. Data encryption

Mark S. Schmalz, 1994, Defense, Security, and Sensing.

SEEKing Knowledge in Legacy Information Systems to Support Interoperability

Joachim Hammer, Mark S. Schmalz, Sangeetha Shekar, 2002 .

Knowledge Extraction in the SEEK Project Part I: Data Reverse Engineering

Joachim Hammer, Mark S. Schmalz, S. Shekar, 2002 .

An Overview of World Wide Web Search Technologies

Gerhard X. Ritter, Wen-Chen Hu, Mark S. Schmalz, 2001 .

Boundary representation techniques for object-based image compression

Gerhard X. Ritter, Mark S. Schmalz, G. Ritter, 2004, SPIE Optics + Photonics.

EFFICIENT AUTONOMOUS ENDMEMBER DETERMINATION USING LATTICE AUTO-ASSOCIATIVE MEMORIES

Gerhard X. Ritter, Mark S. Schmalz, Gonzalo Urcid, 2007 .

Optimizing push/pull envelopes for energy-efficient cloud-sensor systems

Abdelsalam Helal, My T. Thai, Yi Xu, 2011, MSWiM '11.

Image-algebraic design of multispectral target recognition algorithms

Gerhard X. Ritter, Mark S. Schmalz, G. Ritter, 1994, Optics & Photonics.

Reconstruction of submerged targets from multiple airborne images: II. Algorithms and simulation results

Mark S. Schmalz, 1999, Optics & Photonics.

A framework for rendering high resolution synthetic aperture radar images on heterogeneous architectures

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2014, 2014 IEEE Symposium on Computers and Communications (ISCC).

Algorithms for the detection of chewing behavior in dietary monitoring applications

Abdelsalam Helal, Mark S. Schmalz, Andres Mendez-Vasquez, 2009, Optical Engineering + Applications.

Image Algebra Matlab language version 2.3 for image processing and compression research

Gerhard X. Ritter, Mark S. Schmalz, Eric Hayden, 2010, Optical Engineering + Applications.

Mathematics and applications of data/image coding, compression, and encryption III : 2 August 2000, San Diego, USA

Mark S. Schmalz, 2000 .

Stereophotogrammetry of the sea surface: an introduction

Mark S. Schmalz, 1993, Defense, Security, and Sensing.

Efficient imaging with integrated optoelectronics: II. Massively parallel analog vision chip

Joseph N. Wilson, Gerhard X. Ritter, Mark S. Schmalz, 1998, Other Conferences.

Efficient imaging with integrated optoelectronics: I. Overview and some applications

Joseph N. Wilson, Gerhard X. Ritter, James G. Fleming, 1998, Other Conferences.

Processing of compressed imagery: multitarget image processing with VPIC-, BTC-, VQ-, and JPEG-compressed imagery

Mark S. Schmalz, 1996, Defense, Security, and Sensing.

Compressive Computation and Moore's Law

Mark S. Schmalz, 2003, SPIE Optics + Photonics.

Adaptive wireless thin-client model for mobile computing

Abdelsalam Helal, Mark S. Schmalz, Mohammad Al-Turkistany, 2009 .

Single-instruction multiple-data (SIMD) parallel optical computation of high-level image operations

Mark S. Schmalz, 1994, Defense, Security, and Sensing.

Introduction to the local enhancement of underwater imagery

Mark S. Schmalz, 1995, Defense, Security, and Sensing.

Power-and space-efficient image computation with compressive processing: II. Models and simulation results

Mark S. Schmalz, 2000, SPIE Optics + Photonics.

Optical and electro-optical architectures for the compression and encryption of discrete signals and imagery: 1. Data compression

Mark S. Schmalz, 1994, Defense, Security, and Sensing.

Manyscale Computing for Sensor Processing in Support of Space Situational Awareness

Sartaj Sahni, Sanjay Ranka, Mark S. Schmalz, 2014 .

Reconstruction of submerged targets from multiple airborne images: I. Theory and error analysis

Mark S. Schmalz, 1999, Optics & Photonics.

Knowledge Extraction in the SEEK Project Part II: Extracting Meaning from Legacy Application Code through Pattern Matching

Joachim Hammer, Oguzhan Topsakal, Mark S. Schmalz, 2003 .

Ranging and recognition of small targets in compressed stereoscopic imagery: I. Background and theory

Mark S. Schmalz, 1996, Optics & Photonics.

Processing of compressed imagery: basic theory with visual pattern image coding (VPIC) and block truncation coding (BTC) transformations

Mark S. Schmalz, 1996, Defense, Security, and Sensing.

Performance analysis of compression algorithms for noisy multispectral underwater images of small targets

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 1997, Defense, Security, and Sensing.

Local analysis of distortion and ATR error associated with decompressed digital imagery

Gerhard X. Ritter, Frank M. Caimi, Mark S. Schmalz, 2001, SPIE Optics + Photonics.

Errors inherent in reconstruction of obscured targets for multilook imagery: I. Error analysis and simulation results

Mark S. Schmalz, 1998, Defense, Security, and Sensing.

Automated analysis and prediction of accuracy and performance in ATR algorithms: I. Requirements, theory, and software implementation

Mark S. Schmalz, 1997, Defense, Security, and Sensing.

Dynamic multistatic synthetic aperture radar (DMSAR) with image reconstruction algorithms and analysis

Sartaj Sahni, Guna Seetharaman, Sanjay Ranka, 2013, 2013 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

Mathematical methods for mapping image and data compression transforms to adaptive computing systems

Mark S. Schmalz, E. X. Ritter, F. H. Caimi, 1998, IEEE Oceanic Engineering Society. OCEANS'98. Conference Proceedings (Cat. No.98CH36259).

Introduction to the Book

Bessam Abdulrazak, Sumi Helal, Mounir Mokhtari, 2008 .

Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI

Jaakko Astola, Junior Barrera, Gerhard X. Ritter, 2017 .

Mathematics of Data/ Image Pattern Recognition, Compression, Coding, and Encryption X, With Applications

Jaakko Astola, Junior Barrera, Gerhard X. Ritter, 2007 .