Ophthalmology

Paddy Disease Detection and Classification Using Computer Vision Techniques: A Mobile Application to Detect Paddy Disease

Plant diseases significantly impact our food supply, causing problems for farmers, economies reliant on agriculture, and global food security. Accurate and timely plant disease diagnosis is crucial for effective treatment and minimizing yield losses. Despite advancements in agricultural technology, a precise and early diagnosis remains a challenge, especially in underdeveloped regions where agri...

RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

Remote Sensing Vision-Language Models (RS VLMs) have made much progress in the tasks of remote sensing (RS) image comprehension. While performing well in multi-modal reasoning and multi-turn conversations, the existing models lack pixel-level understanding and struggle with multi-image inputs. In this work, we propose RSUniVLM, a unified, end-to-end RS VLM designed for comprehensive vision under...

Multimodal Biometric Authentication Using Camera-Based PPG and Fingerprint Fusion

Camera-based photoplethysmography (PPG) obtained from smartphones has shown great promise for personalized healthcare and secure authentication. Thi...

Not Just Text: Uncovering Vision Modality Typographic Threats in Image Generation Models

Current image generation models can effortlessly produce high-quality, highly realistic images, but this also increases the risk of misuse. In vario...

Automated Dynamic Image Analysis for Particle Size and Shape Classification in Three Dimensions

We introduce OCULAR, an innovative hardware and software solution for three-dimensional dynamic image analysis of fine particles. Current state-of-t...

From classical techniques to convolution-based models: A review of object detection algorithms

Object detection is a fundamental task in computer vision and image understanding, with the goal of identifying and localizing objects of interest w...

Superpixel Tokenization for Vision Transformers: Preserving Semantic Integrity in Visual Tokens

Transformers, a groundbreaking architecture proposed for Natural Language Processing (NLP), have also achieved remarkable success in Computer Vision...

Superposition through Active Learning lens

Superposition or Neuron Polysemanticity are important concepts in the field of interpretability and one might say they are these most intricately be...

Assessing and Learning Alignment of Unimodal Vision and Language Models

How well are unimodal vision and language models aligned? Although prior work have approached answering this question, their assessment methods do n...

Aberration Correcting Vision Transformers for High-Fidelity Metalens Imaging

Metalens is an emerging optical system with an irreplaceable merit in that it can be manufactured in ultra-thin and compact sizes, which shows great...

MageBench: Bridging Large Multimodal Models to Agents

LMMs have shown impressive visual understanding capabilities, with the potential to be applied in agents, which demand strong reasoning and planning...

VisionZip: Longer is Better but Not Necessary in Vision Language Models

Recent advancements in vision-language models have enhanced performance by increasing the length of visual tokens, making them much longer than text...

Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion

We present Florence-VL, a new family of multimodal large language models (MLLMs) with enriched visual representations produced by Florence-2, a gene...

VladVA: Discriminative Fine-tuning of LVLMs

Contrastively-trained Vision-Language Models (VLMs) like CLIP have become the de facto approach for discriminative vision-language representation le...

Reflective Teacher: Semi-Supervised Multimodal 3D Object Detection in Bird's-Eye-View via Uncertainty Measure

Applying pseudo labeling techniques has been found to be advantageous in semi-supervised 3D object detection (SSOD) in Bird's-Eye-View (BEV) for aut...

Liquid: Language Models are Scalable and Unified Multi-modal Generators

We present Liquid, an auto-regressive generation paradigm that seamlessly integrates visual comprehension and generation by tokenizing images into d...

LL-ICM: Image Compression for Low-level Machine Vision via Large Vision-Language Model

Image Compression for Machines (ICM) aims to compress images for machine vision tasks rather than human viewing. Current works predominantly concent...

Designing DNNs for a trade-off between robustness and processing performance in embedded devices

Machine learning-based embedded systems employed in safety-critical applications such as aerospace and autonomous driving need to be robust against ...

DiffuPT: Class Imbalance Mitigation for Glaucoma Detection via Diffusion Based Generation and Model Pretraining

Glaucoma is a progressive optic neuropathy characterized by structural damage to the optic nerve head and functional changes in the visual field. De...

FLAIR: VLM with Fine-grained Language-informed Image Representations

CLIP has shown impressive results in aligning images and texts at scale. However, its ability to capture detailed visual features remains limited be...