NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar

Autor: Guan, Runwei, Liu, Jianan, Jia, Liye, Zhao, Haocheng, Yao, Shanliang, Zhu, Xiaohui, Man, Ka Lok, Lim, Eng Gee, Smith, Jeremy, Yue, Yutao

Recently, visual grounding and multi-sensors setting have been incorporated into perception system for terrestrial autonomous driving systems and Unmanned Surface Vehicles (USVs), yet the high complexity of modern learning-based visual grounding mode

Externí odkaz: http://arxiv.org/abs/2408.17207

The need to implement FAIR principles in biomolecular simulations

Autor: Amaro, Rommie, Åqvist, Johan, Bahar, Ivet, Battistini, Federica, Bellaiche, Adam, Beltran, Daniel, Biggin, Philip C., Bonomi, Massimiliano, Bowman, Gregory R., Bryce, Richard, Bussi, Giovanni, Carloni, Paolo, Case, David, Cavalli, Andrea, Chang, Chie-En A., Cheatham III, Thomas E., Cheung, Margaret S., Chipot, Cris, Chong, Lillian T., Choudhary, Preeti, Cisneros, Gerardo Andres, Clementi, Cecilia, Collepardo-Guevara, Rosana, Coveney, Peter, Covino, Roberto, Crawford, T. Daniel, Peraro, Matteo Dal, de Groot, Bert, Delemotte, Lucie, De Vivo, Marco, Essex, Jonathan, Fraternali, Franca, Gao, Jiali, Gelpí, Josep Lluís, Gervasio, Francesco Luigi, Gonzalez-Nilo, Fernando Danilo, Grubmüller, Helmut, Guenza, Marina, Guzman, Horacio V., Harris, Sarah, Head-Gordon, Teresa, Hernandez, Rigoberto, Hospital, Adam, Huang, Niu, Huang, Xuhui, Hummer, Gerhard, Iglesias-Fernández, Javier, Jensen, Jan H., Jha, Shantenu, Jiao, Wanting, Jorgensen, William L., Kamerlin, Shina Caroline Lynn, Khalid, Syma, Laughton, Charles, Levitt, Michael, Limongelli, Vittorio, Lindahl, Erik, Lindorff-Larsen, Kresten, Loverde, Sharon, Lundborg, Magnus, Luo, Yun Lyna, Luque, Francisco Javier, Lynch, Charlotte I., MacKerell, Alexander, Magistrato, Alessandra, Marrink, Siewert J., Martin, Hugh, McCammon, J. Andrew, Merz, Kenneth, Moliner, Vicent, Mulholland, Adrian, Murad, Sohail, Naganathan, Athi N., Nangia, Shikha, Noe, Frank, Noy, Agnes, Oláh, Julianna, O'Mara, Megan, Ondrechen, Mary Jo, Onuchic, José N., Onufriev, Alexey, Osuna, Silvia, Panchenko, Anna R., Pantano, Sergio, Parish, Carol, Parrinello, Michele, Perez, Alberto, Perez-Acle, Tomas, Perilla, Juan R., Pettitt, B. Montgomery, Pietropalo, Adriana, Piquemal, Jean-Philip, Poma, Adolfo, Praprotnik, Matej, Ramos, Maria J., Ren, Pengyu, Reuter, Nathalie, Roitberg, Adrian, Rosta, Edina, Rovira, Carme, Roux, Benoit, Röthlisberger, Ursula, Sanbonmatsu, Karissa Y., Schlick, Tamar, Shaytan, Alexey K., Simmerling, Carlos, Smith, Jeremy C., Sugita, Yuji, Świderek, Katarzyna, Taiji, Makoto, Tao, Peng, Tikhonova, Irina G., Tirado-Rives, Julian, Tunón, Inaki, Van Der Kamp, Marc W., Van der Spoel, David, Velankar, Sameer, Voth, Gregory A., Wade, Rebecca, Warshel, Ariel, Welborn, Valerie Vaissier, Wetmore, Stacey, Wong, Chung F., Yang, Lee-Wei, Zacharias, Martin, Orozco, Modesto

This letter illustrates the opinion of the molecular dynamics (MD) community on the need to adopt a new FAIR paradigm for the use of molecular simulations. It highlights the necessity of a collaborative effort to create, establish, and sustain a data

Externí odkaz: http://arxiv.org/abs/2407.16584

Hierarchical Stage-Wise Training of Linked Deep Neural Networks for Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi RSSI Fingerprinting

Autor: Li, Sihao, Kim, Kyeong Soo, Tang, Zhe, Graduate, Smith, Jeremy S.

Publikováno v: IEEE Sensors Journal, Early Access, 12 September 2024

In this paper, we present a new solution to the problem of large-scale multi-building and multi-floor indoor localization based on linked neural networks, where each neural network is dedicated to a sub-problem and trained under a hierarchical stage-

Externí odkaz: http://arxiv.org/abs/2407.13288

Referring Flexible Image Restoration

Autor: Guan, Runwei, Hu, Rongsheng, Zhou, Zhuhao, Xue, Tianlang, Man, Ka Lok, Smith, Jeremy, Lim, Eng Gee, Ding, Weiping, Yue, Yutao

In reality, images often exhibit multiple degradations, such as rain and fog at night (triple degradations). However, in many cases, individuals may not want to remove all degradations, for instance, a blurry lens revealing a beautiful snowy landscap

Externí odkaz: http://arxiv.org/abs/2404.10342

Static vs. Dynamic Databases for Indoor Localization based on Wi-Fi Fingerprinting: A Discussion from a Data Perspective

Autor: Tang, Zhe, Gu, Ruocheng, Li, Sihao, Kim, Kyeong Soo, Smith, Jeremy S.

Wi-Fi fingerprinting has emerged as the most popular approach to indoor localization. The use of ML algorithms has greatly improved the localization performance of Wi-Fi fingerprinting, but its success depends on the availability of fingerprint datab

Externí odkaz: http://arxiv.org/abs/2402.12756