10 accepted papers
Classifier-Free Guidance (CFG) is a cornerstone of modern text-to-image models, yet its reliance on a semantically vacuous null prompt generates a guidance signal prone to geometric entanglement. This is a key factor limiting its precision, leading to well-documented failures in complex compositiona
Deep neural networks (DNNs) typically employ an end-to-end (E2E) training paradigm which presents several challenges, including high GPU memory consumption, inefficiency, and difficulties in model parallelization during training. Recent research has sought to address these issues, with one promising…
Neural Architecture Search (NAS) methods seek effective optimization toward performance metrics regarding model accuracy and generalization while facing challenges regarding search costs and GPU resources. Recent Neural Tangent Kernel (NTK) NAS methods achieve remarkable search efficiency based on a…
Deep learning has been successfully used to automate the modeling process that trains a network/model from a given experimental dataset to calculate the output directly using high-dimensional complex raw data. However, the trained network is an inverse of the welding process (forward process) that p
Recently, a series of works have looked into further improving the adapter-based tuning by manually designing better adapter architectures. Understandably, these manually designed solutions are sub-optimal. In this work, we propose the Learned Adapter framework to automatically learn the optimal ada…
This letter illustrates how a challenging problem be solved by assuring the adequacy of the raw information and using an appropriate deep learning network to extract the relevant information. The problem concerned is accurate monitoring of the penetration, in a fully penetrated weld pool, as quantif
Geometrical information of the 3D weld pool surface provides clues to determine the penetration state whose monitoring and feedback control are crucial for critical applications involving high temperatures and pressures. In this letter, a biprism stereo vision system is established to sense the weld
Weld pool penetration is a major indicator of weld integrity but it is not directly measurable. The key to solving this issue is to find or create observable phenomena that can be used to derive the penetration. An innovative method has recently been proposed/developed to derive the penetration from
This letter presents a virtual reality (VR) human–robot interaction welding system that allows human welders to manipulate a welding robot and undertake welding tasks naturally and intuitively via consumer-grade VR hardware (HTC Vive). In this system, human welders’ operations are captured by motion
In arc welding processes, real time control algorithms have to be developed in order to achieve desired weld quality. However, there could exist big uncertainties and noise in the process, which nullifies the conventional online control method. Besides, due to the modelling difficulty and low experi…