A complete survey on generative ai (aigc): Is chatgpt from gpt-4 to gpt-5 all you need?
As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …
everywhere because of its ability to analyze and create text, images, and beyond. With such …
One small step for generative ai, one giant leap for agi: A complete survey on chatgpt in aigc era
OpenAI has recently released GPT-4 (aka ChatGPT plus), which is demonstrated to be one
small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI) …
small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI) …
Faster segment anything: Towards lightweight sam for mobile applications
Segment anything model (SAM) is a prompt-guided vision foundation model for cutting out
the object of interest from its background. Since Meta research team released the SA project …
the object of interest from its background. Since Meta research team released the SA project …
Cloob: Modern hopfield networks with infoloob outperform clip
CLIP yielded impressive results on zero-shot transfer learning tasks and is considered as a
foundation model like BERT or GPT3. CLIP vision models that have a rich representation are …
foundation model like BERT or GPT3. CLIP vision models that have a rich representation are …
A survey on masked autoencoder for self-supervised learning in vision and beyond
Masked autoencoders are scalable vision learners, as the title of MAE\cite {he2022masked},
which suggests that self-supervised learning (SSL) in vision might undertake a similar …
which suggests that self-supervised learning (SSL) in vision might undertake a similar …
Variational gated autoencoder-based feature extraction model for inferring disease-miRNA associations based on multiview features
Y Guo, D Zhou, X Ruan, J Cao - Neural Networks, 2023 - Elsevier
MicroRNAs (miRNA) play critical roles in diverse biological processes of diseases. Inferring
potential disease-miRNA associations enable us to better understand the development and …
potential disease-miRNA associations enable us to better understand the development and …
Firerisk: A remote sensing dataset for fire risk assessment with benchmarks using supervised and self-supervised learning
S Shen, S Seneviratne, X Wanyan… - … Conference on Digital …, 2023 - ieeexplore.ieee.org
In recent decades, wildfires have caused tremendous property losses, fatalities, and
extensive damage to forest ecosystems. Inspired by the abundance of publicly available …
extensive damage to forest ecosystems. Inspired by the abundance of publicly available …
Domainadaptor: A novel approach to test-time adaptation
To deal with the domain shift between training and test samples, current methods have
primarily focused on learning generalizable features during training and ignore the …
primarily focused on learning generalizable features during training and ignore the …
On the duality between contrastive and non-contrastive self-supervised learning
Recent approaches in self-supervised learning of image representations can be categorized
into different families of methods and, in particular, can be divided into contrastive and non …
into different families of methods and, in particular, can be divided into contrastive and non …
Adamae: Adaptive masking for efficient spatiotemporal learning with masked autoencoders
Abstract Masked Autoencoders (MAEs) learn generalizable representations for image, text,
audio, video, etc., by reconstructing masked input data from tokens of the visible data …
audio, video, etc., by reconstructing masked input data from tokens of the visible data …