Spherical mask: coarse-to-fine 3D point cloud instance segmentation with spherical representation by Shin, S, Zhou, K, Vankadari, M, Markham, A, Trigoni, N

“…Coarse-to-fine 3D instance segmentation methods show weak performances compared to recent Grouping-based, Kernel-based and Transformer-based methods. …”

Markov-Chain Monte Carlo Sampling of Visibility Boundaries for Differentiable Rendering by Xu, Peiyu, Bangaru, Sai, Li, Tzu-Mao, Zhao, Shuang

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Efficient sampling for extreme event statistics of the wave loads on an offshore platform by Mohamad, Mustafa A., Sapsis, Themistoklis P.

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Detecting adversarial samples for deep neural networks through mutation testing by Tan, Kye Yen

“…Adversarial attacks are malicious modifications made on input samples to the DNN that causes the DNN to fail at its task. …”
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Effects of statistical sampling errors on flood-damage-reduction project evaluation by Su, Hsin-Ting, Tung, Yeou-Koung

“…A Monte Carlo simulation is applied in the study to simulate the epistemic uncertainty associated with the sampling error of the flood magnitude. The model parameter uncertainty is explicitly considered in the estimation of statistical features of flood damage. …”
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A first study of compressive sensing for side-channel leakage sampling by Ou, Changhai, Zhou, Chengju, Lam, Siew-Kei

“…However, as the operating frequency of cryptographic devices continues to increase due to advancing technology, leakage sampling will impose higher requirements on the sampling rate and storage capacity of the sampling equipment. …”
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Performance and microstructure of carbonated MgO samples under high temperatures by Pu, Liyun, Unluer, Cise

“…This study investigated the changes in the performance and microstructure of carbonated MgO samples subjected to 40°C–550°C in water, oven, and furnace conditions. …”
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Environmental stress and emotional reactivity: an exploratory experience sampling method study by Wong, Corine Sau Man, Chan, Wai Chi, Lo, Kristen Wing Yan, Chen, Eric Yu Hai, Lam, Linda Chiu Wa

“…Our study aimed to fill this gap by examining how daily ES affects momentary emotional reactivity using experience sampling method (ESM). Methods: Participants were randomly recruited from a prospective cohort study in Hong Kong to participate in a 7-day ESM study. …”
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The small-sample problem in content-based image retrieval with relevance feedback by Wang, Lei.

“…To improve the performance of content-based image retrieval with relevance feedback by tackling the small-sample problem in learning and retrieval.…”
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An ultra low-power precision sample-and-hold circuit for biomedical application by Mah, Sai Lei

“…In this project, the student was able to realize a low-power precision sample-and-hold (S/H) circuit for biomedical application based on switched-capacitor circuit. …”
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Application of COLD-PCR for improved detection of EGFR mutations in clinical samples. by Zhang, Zhi Xuan.

“…After COLD-PCR and sequencing analysis of 30 samples, this study did not detect any new mutations in the samples when COLD-PCR was used and no significant overall increase in the ratio of mutant to wild type alleles was observed. …”
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Monkeypox virus isolation from longitudinal samples in 11 hospitalised patients by Callaby, H, Olver, J, Emery, K, Richards, KS, Killip, M, Groves, N, Beadsworth, MBJ, Price, DA, Cooke, GS, Collini, P, Cole, J, Dunning, J, Semple, MG, Baillie, JK, ISARIC4C Investigators, Rampling, T, Houlihan, CF

Development of HDX-MS methods to further investigate complex protein samples by Smith, L

A broadband ferromagnetic resonance dipper probe for magnetic damping measurements from 4.2 K to 300 K by He, Shikun, Panagopoulos, Christos

Subjects: “…Sample handling…”
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An Effective Med-VQA Method Using a Transformer with Weights Fusion of Multiple Fine-Tuned Models by Al-Hadhrami, Suheer, Menai, Mohamed El Bachir, Al-Ahmadi, Saad, Alnafessah, Ahmad

“…The second model, the greedy-soup-based model, uses a greedy soup technique based on the fusion of multiple fine-tuned models to set the model parameters. The greedy soup selects the model parameters by fusing the model parameters that have significant performance on the validation accuracy in training. …”
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Evaluating Adaptive Layer Freezing through Hyperparameter Optimization for Enhanced Fine-Tuning Performance of Language Models by Figueroa, Reinaldo

“…When dealing with data scarcity, transfer learning has become the go-to method to use these models in specialized downstream tasks via fine-tuning. However, fine-tuning on small datasets can lead to overfitting and a lack of generalization. …”
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EyeTrAES: Fine-grained, Low-Latency Eye Tracking via Adaptive Event Slicing by Sen, Argha, Bandara, Nuwan, Gokarn, Ila, Kandappu, Thivya, Misra, Archan

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Fine-tuning selective layer architecture of hydrogel membrane towards high separation performances for engineered osmosis by Qin, Detao, Liu, Zhaoyang, Bai, Hongwei, Song, Xiaoxiao, Li, Zhengtao, Sun, Darren Delai

“…Towards this goal, the architecture of hydrogel selective layer is finely tuned for the first time for improving engineered osmosis (EO) membrane performance. …”
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Enhancing Landsat image based aboveground biomass estimation of black locust with scale bias-corrected LiDAR AGB map and stratified sampling by Qin, Shuhong, Wang, Hong, Li, Xiuneng, Gao, Jay, Jin, Jiaxin, Li, Yongtao, Lu, Jinbo, Meng, Pengyu, Sun, Jing, Song, Zhenglin, Donev, Petar, Ma, Zhangfeng

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HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling by Huang, Xin, Rosman, Guy, Gilitschenski, Igor, Jasour, Ashkan, McGill, Stephen G., Leonard, John J., Williams, Brian C.

“…We learn the probabilistic hybrid model via a maximum likelihood estimation problem and leverage neural proposal distributions to sample adaptively from the exponentially growing discrete space. …”
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