Chaw, J.K.[Jun Kit]
* 2017: Analysis of produce recognition system with taxonomist's knowledge using computer vision and different classifiers
Includes: Chaw, J.K.[Jun Kit] Chaw, J.K.[Jun-Kit]
Chaware, A.[Amey]
* 2021: Physics-Enhanced Machine Learning for Virtual Fluorescence Microscopy
Chawarski, J.[Julek]
* 2023: Detecting Underwater Discrete Scatterers in Echograms with Deep Learning-Based Semantic Segmentation
Chawathe, M.
* 2001: Compiling SA-C Programs to FPGAs: Performance Results
* 2002: Implementing image applications on FPGAs
* 2003: Accelerated image processing on FPGAs
Chawda, A.[Ajay]
* 2023: Quantifiable Robustness Estimation for Object Detection with CNNs Using Intrinsic Dimensionality
Chawda, B.
* 2015: Being Aware of the World: Toward Using Social Media to Support the Blind With Navigation
Chawda, P.
* 2004: Adaptive 2.5D visual servoing of cartesian robots
* 2005: Homography-based visual servo regulation of mobile robots
Chawdhary, A.[Aziem]
* 2015: Revisiting Volgenant-Jonker for Approximating Graph Edit Distance
* 2017: Optimising the Volgenant-Jonker algorithm for approximating graph edit distance
Chawla, A.
* 2018: Automatic Optic Disk and Cup Segmentation of Fundus Images Using Deep Learning
* 2021: Data-free Knowledge Distillation for Object Detection
Includes: Chawla, A. Chawla, A.[Akshay]
Chawla, A.K.
* 2013: Reverse scan for transform skip mode in HEVC codec
Chawla, G.[Gaurav]
* 2022: Practical and Scalable Desktop-Based High-Quality Facial Capture
Chawla, H.[Hemang]
* 2024: Continual Learning of Unsupervised Monocular Depth from Videos
Chawla, K.[Kunal]
* 2018: Attention-Based Ensemble for Deep Metric Learning
Chawla, M.
* 2019: Disguised Faces in the Wild 2019
Chawla, N.[Nitesh]
* 2001: Bagging Is a Small-Data-Set Phenomenon
* 2016: Orlando Project: A 28 nm FD-SOI Low Memory Embedded Neural Network ASIC, The
* 2021: Computational Imaging in 3D X-Ray Microscopy: Reconstruction, Image Segmentation and Time-Evolved Experiments
Includes: Chawla, N.[Nitesh] Chawla, N.[Nitin] Chawla, N.[Nikhilesh]
Chawla, N.V.[Nitesh V.]
* 2003: Distributed learning with bagging-like performance
* 2005: Random Subspaces and Subsampling for 2-D Face Recognition
* 2007: Learning to predict gender from iris images
* 2009: SVMs Modeling for Highly Imbalanced Classification
* 2010: Identifying and evaluating community structure in complex networks
* 2010: Incremental Learning Algorithm for Non-stationary Environments and Class Imbalance, An
* 2012: unifying view on dataset shift in classification, A
* 2023: Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows
Includes: Chawla, N.V.[Nitesh V.] Chawla, N.V.
8 for Chawla, N.V.
Chawla, P.[Pranit]
* 2021: Leveraging Style and Content features for Text Conditioned Image Retrieval
* 2022: SAC: Semantic Attention Composition for Text-Conditioned Image Retrieval
Chawla, S.
* 1997: Significance Tree Quantization of the Discrete Cosine Transform
* 1999: Object Model of Direction and Its Implications, An
* 2018: RoadTracer: Automatic Extraction of Road Networks from Aerial Images
* 2019: Incremental commute time and its online applications
* 2020: Sat2graph: Road Graph Extraction Through Graph-tensor Encoding
* 2021: Inferring and Improving Street Maps with Data-Driven Automation
* 2021: Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories
Includes: Chawla, S. Chawla, S.[Sanjay]
7 for Chawla, S.