A recent sensor fusion in a Bird's Eye View (BEV) space has shown its ut...
In continual learning (CL), an AI agent (e.g., autonomous vehicles or
ro...
Existing frameworks for image stitching often provide visually reasonabl...
Trendy suggestions for learning-based elastic warps enable the deep imag...
Min-max routing problems aim to minimize the maximum tour length among a...
This paper proposes Meta-SAGE, a novel approach for improving the scalab...
We study the problem of optimizing biological sequences, e.g., proteins,...
Recently, deep reinforcement learning (DRL) has shown promise in solving...
Modern data augmentation using a mixture-based technique can regularize ...
Split learning (SL) is an emergent distributed learning framework which ...
In this paper, a green, quantized FL framework, which represents data wi...
Modern retrospective analytics systems leverage cascade architecture to
...
Code generation is a longstanding challenge, aiming to generate a code
s...
This paper proposes a novel collaborative distillation meta learning (CD...
In this article, for the first time, we propose a transformer network-ba...
Deploying federated learning (FL) over wireless networks with
resource-c...
Recently, deep reinforcement learning (DRL) frameworks have shown potent...
We propose a novel framework for fine-grained object recognition that le...
Hyperledger Fabric (HLF), one of the most popular private blockchain
pla...
Existing techniques to adapt semantic segmentation networks across the s...
Recent advances in blockchain have led to a significant interest in
deve...
Existing techniques to encode spatial invariance within deep convolution...
The adoption of randomness against heap layout has rendered a good porti...