Flexible image analysis for law enforcement agencies with deep neural networks to determine: where, who and what

Autor: Bouma, Henri, Joosten, Bart, Kruithof, Maarten C, de Boer, Maaike H T, Ginsca, Alexandru, Labbe, Benjamin, Vuong, Quoc T

Publikováno v: SPIE - Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies II, 2018, pp.27

Due to the increasing need for effective security measures and the integration of cameras in commercial products, a hugeamount of visual data is created today. Law enforcement agencies (LEAs) are inspecting images and videos to findradicalization, pr

Externí odkaz: http://arxiv.org/abs/2405.09194

Overcoming limitations in current measures of drug response may enable AI-driven precision oncology

Autor: Katja Ovchinnikova, Jannis Born, Panagiotis Chouvardas, Marianna Rapsomaniki, Marianna Kruithof-de Julio

Publikováno v: npj Precision Oncology, Vol 8, Iss 1, Pp 1-7 (2024)

Abstract Machine learning (ML) models of drug sensitivity prediction are becoming increasingly popular in precision oncology. Here, we identify a fundamental limitation in standard measures of drug sensitivity that hinders the development of personal

Externí odkaz: https://doaj.org/article/0b70ce5cd8e84908af41f9aac145c56b

Apertif, Phased Array Feeds for the Westerbork Synthesis Radio Telescope

Autor: van Cappellen, W. A., Oosterloo, T. A., Verheijen, M. A. W., Adams, E. A. K., Adebahr, B., Braun, R., Hess, K. M., Holties, H., van der Hulst, J. M., Hut, B., Kooistra, E., van Leeuwen, J., Loose, G. M., Morganti, R., Moss, V. A., Orrú, E., Ruiter, M., Schoenmakers, A. P., Vermaas, N. J., Wijnholds, S. J., van Amesfoort, A. S., Arts, M. J., Attema, J. J., Bakker, L., Bassa, C. G., Bast, J. E., Benthem, P., Beukema, R., Blaauw, R., de Blok, W. J. G., Bouwhuis, M., Brink, R. H. van den, Connor, L., Coolen, A. H. W. M., Damstra, S., van Diepen, G. N. J., de Goei, R., Dénes, H., Drost, M., Ebbendorf, N., Frank, B. S., Gardenier, D. W., Gerbers, M., Grange, Y. G., Grit, T., Gunst, A. W., Gupta, N., Ivashina, M. V., Józsa, G. I. G., Janssen, G. H., Koster, A., Kruithof, G. H., Kuindersma, S. J., Kutkin, A., Lucero, D. M., Maan, Y., Maccagni, F. M., van der Marel, J., Mika, A., Morawietz, J., Mulder, H., Mulder, E., Norden, M. J., Offringa, A. R., Oostrum, L. C., Overeem, R. E., Paragi, Z., Pepping, H. J., Petroff, E., Pisano, D. J., Polatidis, A. G., Prasad, P., de Reijer, J. P. R., Romein, J. W., Schaap, J., Schoonderbeek, G. W., Schulz, R., van der Schuur, D., Sclocco, A., Sluman, J. J., Smits, R., Stappers, B. W., Straal, S. M., Stuurwold, K. J. C., Verstappen, J., Vohl, D., Wierenga, K. J., Woestenburg, E. E. M., Zanting, A. W., Ziemke, J.

Publikováno v: A&A 658, A146 (2022)

We describe the APERture Tile In Focus (Apertif) system, a phased array feed (PAF) upgrade of the Westerbork Synthesis Radio Telescope which has transformed this telescope into a high-sensitivity, wide field-of-view L-band imaging and transient surve

Externí odkaz: http://arxiv.org/abs/2109.14234

Osimertinib Plasma Trough Concentration in Relation to Brain Metastases Development in Patients With Advanced EGFR-Mutated NSCLC

Autor: Judith L. Gulikers, MSc, G.D. Marijn Veerman, MD, PhD, Merel Jebbink, MD, PhD, Paul D. Kruithof, PharmD, Christi M.J. Steendam, MD, PhD, René J. Boosman, PhD, Ron H.J. Mathijssen, MD, PhD, Vivianne C.G. Tjan-Heijnen, MD, PhD, Johanna H.M. Driessen, PhD, Safiye Dursun, MD, Egbert F. Smit, MD, PhD, Anne-Marie C. Dingemans, MD, PhD, Robin M.J.M. van Geel, PharmD, PhD, Sander Croes, PharmD, PhD, Lizza E.L. Hendriks, MD, PhD

Publikováno v: JTO Clinical and Research Reports, Vol 5, Iss 4, Pp 100656- (2024)

Introduction: Brain metastases (BM) are common in patients with advanced EGFR-mutated (EGFRm+) NSCLC. Despite good BM-related outcomes of osimertinib, several patients still experience intracranial progression. A possible explanation is pharmacologic

Externí odkaz: https://doaj.org/article/b8cb56c1a21d4838abe7a2a929f0a009

Adversarial Patch Camouflage against Aerial Detection

Autor: Adhikari, Ajaya, Hollander, Richard den, Tolios, Ioannis, van Bekkum, Michael, Bal, Anneloes, Hendriks, Stijn, Kruithof, Maarten, Gross, Dennis, Jansen, Nils, Pérez, Guillermo, Buurman, Kit, Raaijmakers, Stephan

Detection of military assets on the ground can be performed by applying deep learning-based object detectors on drone surveillance footage. The traditional way of hiding military assets from sight is camouflage, for example by using camouflage nets.

Externí odkaz: http://arxiv.org/abs/2008.13671