76 citations · 245 across the 28 of their papers we have counts for
33 papers
DualMiT-Net: Local-Global Transformer-Convolutional Fusion for Breast Mass Segmentation in Mammographic Regions of Interest
Alibek Kamiluly, Milana Muratova, Yash Patel +1
Breast mass segmentation is an important step in computer-aided mammography, but it remains difficult because masses can have low contrast, irregular shapes, and boundaries that bl…
Secure-by-Disguise: A Systematic Evaluation of Image Disguising for Confidential Medical Image Modeling
Jason Rojas, Jiajie He, Yash Patel +3
Cloud-based deep learning enables large-scale medical image analysis but raises significant privacy concerns when sensitive patient images are outsourced for model development. Ima…
Information-Regularized Attention for Visual-Centric Reasoning
Guohao Sun, Xiaofang Wang, Yash Patel +3
Vision-language models (VLMs) have become a paradigm for multimodal learning, yet remain unstable due to object hallucination, weak visual grounding, and catastrophic forgetting af…
Integrated Image and Location Analysis for Wound Classification: A Deep Learning Approach
Yash Patel, Tirth Shah, Mrinal Kanti Dhar +4
The global burden of acute and chronic wounds presents a compelling case for enhancing wound classification methods, a vital step in diagnosing and determining optimal treatments.…
Diffusion Models for Probabilistic Deconvolution of Galaxy Images
Zhiwei Xue, Yuhang Li, Yash Patel +1
Telescopes capture images with a particular point spread function (PSF). Inferring what an image would have looked like with a much sharper PSF, a problem known as PSF deconvolutio…
Neural Network Training and Non-Differentiable Objective Functions
Yash Patel
Many important computer vision tasks are naturally formulated to have a non-differentiable objective. Therefore, the standard, dominant training procedure of a neural network is no…
FUSegNet: A Deep Convolutional Neural Network for Foot Ulcer Segmentation
Mrinal Kanti Dhar, Taiyu Zhang, Yash Patel +2
This paper presents FUSegNet, a new model for foot ulcer segmentation in diabetes patients, which uses the pre-trained EfficientNet-b7 as a backbone to address the issue of limited…
SimCon Loss with Multiple Views for Text Supervised Semantic Segmentation
Yash Patel, Yusheng Xie, Yi Zhu +2
Learning to segment images purely by relying on the image-text alignment from web data can lead to sub-optimal performance due to noise in the data. The noise comes from the sample…
DocILE Benchmark for Document Information Localization and Extraction
Štěpán Šimsa, Milan Šulc, Michal Uřičář +8
This paper introduces the DocILE benchmark with the largest dataset of business documents for the tasks of Key Information Localization and Extraction and Line Item Recognition. It…
DocILE 2023 Teaser: Document Information Localization and Extraction
Štěpán Šimsa, Milan Šulc, Matyáš Skalický +2
The lack of data for information extraction (IE) from semi-structured business documents is a real problem for the IE community. Publications relying on large-scale datasets use on…
MultiNet with Transformers: A Model for Cancer Diagnosis Using Images
Hosein Barzekar, Yash Patel, Ling Tong +1
Cancer is a leading cause of death in many countries. An early diagnosis of cancer based on biomedical imaging ensures effective treatment and a better prognosis. However, biomedic…
Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training
Filip Radenovic, Abhimanyu Dubey, Abhishek Kadian +6
Vision-language models trained with contrastive learning on large-scale noisy data are becoming increasingly popular for zero-shot recognition problems. In this paper we improve th…
Generalized Differentiable RANSAC
Tong Wei, Yash Patel, Alexander Shekhovtsov +2
We propose -RANSAC, a generalized differentiable RANSAC that allows learning the entire randomized robust estimation pipeline. The proposed approach enables the use of rela…
Scalable Bayesian Inference for Finding Strong Gravitational Lenses
Yash Patel, Jeffrey Regier
Finding strong gravitational lenses in astronomical images allows us to assess cosmological theories and understand the large-scale structure of the universe. Previous works on len…
Contrastive Classification and Representation Learning with Probabilistic Interpretation
Rahaf Aljundi, Yash Patel, Milan Sulc +2
Cross entropy loss has served as the main objective function for classification-based tasks. Widely deployed for learning neural network classifiers, it shows both effectiveness an…
Reinforcement Learning Assisted Recursive QAOA
Yash J. Patel, Sofiene Jerbi, Thomas Bäck +1
Variational quantum algorithms such as the Quantum Approximation Optimization Algorithm (QAOA) in recent years have gained popularity as they provide the hope of using NISQ devices…
Wound Severity Classification using Deep Neural Network
D. M. Anisuzzaman, Yash Patel, Jeffrey Niezgoda +2
The classification of wound severity is a critical step in wound diagnosis. An effective classifier can help wound professionals categorize wound conditions more quickly and afford…
Multi-modal Wound Classification using Wound Image and Location by Deep Neural Network
D. M. Anisuzzaman, Yash Patel, Behrouz Rostami +3
Wound classification is an essential step of wound diagnosis. An efficient classifier can assist wound specialists in classifying wound types with less financial and time costs and…
Recall@k Surrogate Loss with Large Batches and Similarity Mixup
Yash Patel, Giorgos Tolias, Jiri Matas
This work focuses on learning deep visual representation models for retrieval by exploring the interplay between a new loss function, the batch size, and a new regularization appro…
FEDS -- Filtered Edit Distance Surrogate
Yash Patel, Jiri Matas
This paper proposes a procedure to train a scene text recognition model using a robust learned surrogate of edit distance. The proposed method borrows from self-paced learning and…
Neural Network-based Acoustic Vehicle Counting
Slobodan Djukanović, Yash Patel, Jiři Matas +1
This paper addresses acoustic vehicle counting using one-channel audio. We predict the pass-by instants of vehicles from local minima of clipped vehicle-to-microphone distance. Thi…
A Mobile App for Wound Localization using Deep Learning
D. M. Anisuzzaman, Yash Patel, Jeffrey Niezgoda +2
We present an automated wound localizer from 2D wound and ulcer images by using deep neural network, as the first step towards building an automated and complete wound diagnostic s…
Learning Surrogates via Deep Embedding
Yash Patel, Tomas Hodan, Jiri Matas
This paper proposes a technique for training a neural network by minimizing a surrogate loss that approximates the target evaluation metric, which may be non-differentiable. The su…
Saliency Driven Perceptual Image Compression
Yash Patel, Srikar Appalaraju, R. Manmatha
This paper proposes a new end-to-end trainable model for lossy image compression, which includes several novel components. The method incorporates 1) an adequate perceptual similar…