20 accepted papers
Extracting singing melody from polyphonic music is an important topic in the field of music information retrieval. In this paper, we propose a singing melody extraction network consisting of five stacked multi-scale feature time-frequency aggregation (MF-TFA) modules. In the same network, deeper lay…
Laminectomy represents an effective surgical procedure for the treatment of lumbar spinal stenosis. Due to the intricate anatomical structure of the lumbar spine, meticulous surgical path planning is essential to ensure the safety of the procedure and enhance the likelihood of successful outcomes. T
Retrosynthesis prediction focuses on identifying reactants capable of synthesizing a target product. Typically, the retrosynthesis prediction involves two phases: Reaction Center Identification and Reactant Generation. However, we argue that most existing methods suffer from two limitations in the t…
Singing melody extraction from polyphonic music is a complex but important task in music information retrieval. Harmonic relationships have been shown to be crucial in this task, but most existing models based on Convolutional Neural Networks (CNNs) struggle to capture long-range harmonic dependenci…
Robotic breast ultrasound (RBUS) aims to standardize breast ultrasonography, reduce the workload of sonographers, and provide high-quality ultrasound (US) images for subsequent diagnosis. In the process of RBUS screening, adjusting the US probe correctly and efficiently to acquire high-quality US im
Percutaneous puncture is a widely used procedure in the diagnosis and therapy of cancer such as biopsy and ablation operations, while the organs in the thoracic and abdominal cavities are significantly affected by patients' respiratory movement. In this study, a robotic puncture system with respirat
Incorporating frame-level phonetic information during the extraction of speaker embeddings has been shown to enhance the performance of speaker verification systems. However, previous studies have primarily relied on phonetic information obtained from pre-trained models of monolingual automatic spee…
Text-to-image diffusion models particularly Stable Diffusion, have revolutionized the field of computer vision. However, the synthesis quality often deteriorates when asked to generate images that faithfully represent complex prompts involving multiple attributes and objects. While previous studies…
We propose a deep neural network with spectrogram matching and mutual attention (SMMA-Net) for audio clue-based target speaker extraction (TSE). To effectively use the auxiliary speech, we proposed spectrogram matching (SM) strategy and mutual attention (MA) block. We conducted all experiments on th…
"Traditional fluorescence staining is phototoxic to live cells, slow, and expensive; thus, the subcellular structure prediction (SSP) from transmitted light (TL) images is emerging as a label-free, faster, low-cost alternative. However, existing approaches utilize 3D networks for one-to-one voxel le…
Multi-modal large language models (MLLMs) have shown impressive capabilities as a general-purpose interface for various visual and linguistic tasks. However, building a unified MLLM for multi-task learning in the medical field remains a thorny challenge. To mitigate the tug-of-war problem of multi-m…
Existing speech separation models based on deep learning typically generalize poorly due to domain mismatch. In this paper, we propose SpeakerAugment (SA), a data augmentation method for generalizable speech separation that aims to increase the diversity of speaker identity in training data, to miti…
Autonomous ultrasound scanning robots have attracted the attention of researchers, and the real-time quality assessment of ultrasound images is the key technology of them. Existing robot systems usually use pixel-level feature statistical methods such as grayscale, confidence map, etc. However, in c
Speech separation dataset typically consists of hard and non-hard samples, and the former is minority and latter majority. The data imbalance problem biases the model towards non-hard samples and weakens the generalization capability. Given that the average separation performance is sufficiently goo…
In endoscopic nasal surgery, robots, rather than surgical assistants, can be introduced to hold endoscopes and act as the surgeon's third hand, which helps to reduce their operation burden. To address the problem of robot-assisted surgical field of view (FOV) acquisition in endoscopic nasal surgery,
We pursue an interpretable pitch tracking model and a jointly trained tone model for Mandarin tone classification. For pitch tracking, present deep learning based pitch model structure seldom considers the Viterbi decoding commonly implemented in prevalent manually designed pitch tracking algorithms…
Natural orifice transluminal endoscopic surgery (NOTES) has received significant attentions due to its minimal incision trauma compared with traditional multi-port robot assisted surgery. Continuum robot can be used in NOTES due to its high flexibility which can adapt to circuitous paths. However, t
In recent years, Siamese trackers have achieved great success in visual tracking. Siamese networks can achieve competitive performance in both accuracy and speed. However, they may suffer from the performance degradation due to the case of large pose variations, out-of-plane, etc. In this paper, we…
Pedicle drilling is a crucial and high-risk process in spinal surgery. Due to the respiration and cardiac cycle, the position of spine would fluctuate during operations, which result in an increase of the difficulty in state recognition of pedicle drilling. To guarantee the safety and validity, a mo…
For a robot serving in a complex environment such as in a restaurant, it is difficult to perform a task like tabletop object manipulation completely by itself, in that some information may be missing. An approach to deal with this is to use a tele-control system and method to control the robot or de…