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Found 14 papers, 4 papers with code
MMCBE: Multi-modality Dataset for Crop Biomass Estimation and Beyond
Addressing this gap, we introduce a new dataset in this domain, i. e. Multi-modality dataset for crop biomass estimation (MMCBE).
Backpropagation-free Network for 3D Test-time Adaptation
Here, we propose a novel method that uses a backpropagation-free approach for TTA for the specific case of 3D data.
RG-CAT: Detection Pipeline and Catalogue of Radio Galaxies in the EMU Pilot Survey
The Gal-DINO network is trained and evaluated on approximately 5, 000 visually inspected radio galaxies and their infrared hosts, encompassing both compact and extended radio morphologies.
DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation
Scene graph generation aims to capture detailed spatial and semantic relationships between objects in an image, which is challenging due to incomplete labelling, long-tailed relationship categories, and relational semantic overlap.
Deep Learning Approaches for Seizure Video Analysis: A Review
Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data; however, there has been limited exploration of their application in evaluating video-based motion detection in the clinical epileptology setting.
A Multimodal Dataset and Benchmark for Radio Galaxy and Infrared Host Detection
We present a novel multimodal dataset developed by expert astronomers to automate the detection and localisation of multi-component extended radio galaxies and their corresponding infrared hosts.
RadioGalaxyNET: Dataset and Novel Computer Vision Algorithms for the Detection of Extended Radio Galaxies and Infrared Hosts
Creating radio galaxy catalogues from next-generation deep surveys requires automated identification of associated components of extended sources and their corresponding infrared hosts.
Ranked #1 on
2D Object Detection
on RadioGalaxyNET Dataset
Hyperbolic Audio-visual Zero-shot Learning
Audio-visual zero-shot learning aims to classify samples consisting of a pair of corresponding audio and video sequences from classes that are not present during training.
Ranked #2 on
GZSL Video Classification
on ActivityNet-GZSL (cls)
Deep Learning for Morphological Identification of Extended Radio Galaxies using Weak Labels
The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts.
Topological Deep Learning: A Review of an Emerging Paradigm
The summaries obtained by these methods are principled global descriptions of multi-dimensional data whilst exhibiting stable properties such as robustness to deformation and noise.
Boundary-aware Instance Segmentation
In this context, existing methods typically propose candidate objects, usually as bounding boxes, and directly predict a binary mask within each such proposal.
Learning to Co-Generate Object Proposals With a Deep Structured Network
In particular, we introduce a deep structured network that jointly predicts the objectness scores and the bounding box locations of multiple object candidates.
Structural Kernel Learning for Large Scale Multiclass Object Co-Detection
To exploit the correlations between objects, we build a fully-connected CRF on the candidates, which explicitly incorporates both geometric layout relations across object classes and similarity relations across multiple images.
