Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks
(DNNs) training, and they usually train a DNN for each single visual recognition task …

As the most fundamental scene understanding tasks, object detection and segmentation
have made tremendous progress in deep learning era. Due to the expensive manual …

The broad learning system (BLS) has recently been applied in numerous fields. However, it
is mainly a supervised learning system and thus not suitable for specific practical …

Camouflaged instance segmentation (CIS) aims to detect and segment objects blending
with their surroundings. While existing CIS methods rely heavily on fully-supervised training …

Abstract Existing approaches to Domain Incremental Learning (DIL) address catastrophic
forgetting by storing and rehearsing exemplars from old domains. However, exemplar-based …

Adversarial attacks in computer vision exploit the vulnerabilities of machine learning models
by introducing subtle perturbations to input data, often leading to incorrect predictions or …

Abstract Vision-Language models (VLMs), ie, image-text pairs of CLIP, have boosted image-
based Deep Learning (DL). Moreover, Visual-Question-Answer (VQA) tools and open …

Abstract Recently large Vision Language (VL) models ie CLIP have demonstrated
impressive capabilities in training solely on internet-scale image-language pairs. Moreover …

Drone-based image processing offers valuable capabilities for surveillance, detection, and
tracking in vast areas, aiding in disaster search and rescue and monitoring artificial events …

This article introduces a novel approach, called causal prompting network (CPNet), to
enhance the causal intervention in the context of image captioning. By leveraging visual …