CHASE
发表于 2025-3-26 22:37:37
1434-9922 rature for many more innovations in ART such as Fuzzy ART, ART2, ART2-a, ARTMAP, ARTMAP-PI, ARTMAP-DS, Gaussian ARTMAP, EXACT ART, and ART-EMAP.978-3-7908-2469-8978-3-7908-1857-4Series ISSN 1434-9922 Series E-ISSN 1860-0808
Glutinous
发表于 2025-3-27 05:06:03
M. Blumecal reasoning and computer science developments also have to be taken into account in identifying problems. Adopting an interdisciplinary approach the book focuses primarily on international humanitarian law, with related ethics and computer science aspects included in the discussion and the analysis.978-3-319-88402-8978-3-319-67266-3
HAIRY
发表于 2025-3-27 07:08:22
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SOB
发表于 2025-3-27 12:50:00
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Conflagration
发表于 2025-3-27 14:00:12
G. Bartfai,R. White are evaluation rules that forbid certain “dehumanized” behavior as a matter of principle; and it is possible that there are imputation rules, the violation of which could lead to persons successfully but unjustifiedly evading their own responsibility. The first avenue will be—after some introductor
长矛
发表于 2025-3-27 18:49:19
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Melatonin
发表于 2025-3-28 00:23:14
C. P. Lim,R. F. Harrisoncal reasoning and computer science developments also have to be taken into account in identifying problems. Adopting an interdisciplinary approach the book focuses primarily on international humanitarian law, with related ethics and computer science aspects included in the discussion and the analysis.978-3-319-88402-8978-3-319-67266-3
GET
发表于 2025-3-28 02:16:46
T. Serrano-Gotarredona,B. Linares-Barrancoe feasible precautions in attack and seeks to determine whether a nation employing autonomous weapons on a battlefield might be able to fully comply. First, this chapter strives to define what is meant by autonomous weapon systems. Second, the chapter will examine the technological advances and oper
旧石器时代
发表于 2025-3-28 09:23:19
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Iatrogenic
发表于 2025-3-28 11:32:56
Incremental Learning and Optimization of Hierarchical Clusterings with Art-Based Modular Networks,oposed earlier by the first author. The network dynamics are specified and some useful properties of both networks are given and then proven. Experiments were carried out on benchmark datasets to demonstrate the representational and learning capabilities of both networks and to compare the developed