Información de la conferencia

ESANN 2027: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

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Día de Entrega:
2026-11-18 Faltan 14 días
Fecha de Notificación:
2027-01-22
Fecha de conferencia:
2027-04-21
Ubicación:
Bruges, Belgium
Ediciones:
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ICORE: B   Vistas: 22172   Seguidores: 6   Asistentes: 1
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Índice Conference Partner (CP-I)

66,5 / 100
Puesto n.º 419 de 5.768 congresos · 8% superior

N.º 31 de 753 en Inteligencia artificial y aprendizaje automático

Reconocimiento académico (35%)
72
Selectividad en la revisión (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Ediciones celebradas (20%)
96
Atención de la comunidad (10%)
37
Integridad del registro público (15%)
55

Datos utilizados: Categorías: ICORE B · Ediciones documentadas: 35 · Investigadores que lo siguen aquí: 6 · Investigadores que abrieron esta página en los últimos 24 meses: 11

Falta en el registro público: Tasas de aceptación históricas (+4,5) · Premios al mejor artículo (+2,3)
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Confianza 80 %: la parte de la puntuación respaldada por datos observados y no por la línea base neutra. Cómo se calcula esta puntuación · Ver la clasificación · Versión del algoritmo 1.2 · Calculado el 2026-11-04

Solicitud de Artículos

ESANN 2027 (European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning) is a ICORE B conference held in Bruges, Belgium on 2027-04-21. The paper submission deadline is 2026-11-18. Acceptance notifications are sent on 2027-01-22.

Scope and topics Since its first happening in 1993, the European Symposium on Artificial Neural Networks has become the reference for researchers on fundamentals and theoretical aspects of artificial neural networks, computational intelligence, machine learning and related topics. Each year, around 100-150 specialists attend ESANN, in order to present their latest results and comprehensive surveys, and to discuss the future developments in this field. The ESANN 2027 conference will follow this tradition, while adapting its scope to the recent developments in the field. The ESANN conferences cover artificial neural networks, machine learning, statistical information processing, and computational intelligence. The central topics of the conferences are the mathematical foundations, algorithms, and ML-AI tools and methodologies for generic use. Applications are not a central focus of the conference; application-oriented papers will only be considered if the scope of possible applications is of generic interest to a large proportion of ESANN participants. Due to the high volume of submissions to AI and machine learning conferences nowadays (including ESANN), a preliminary filter will be applied to submissions before they are sent for review. Therefore, some submissions may be desk-rejected, including those that do not sufficiently align with the scope or expectations of ESANN papers or the interests of participants (regardless of scientific quality). Desk-rejected papers will not be provided with scientific reviews. Authors must be aware of this possibility and adhere to the conditions when submitting their paper. The following is a non-exhaustive list of machine learning, computational intelligence and artificial neural networks topics covered during the ESANN conferences: Neural networks; Deep learning; Kernel machines; Signal processing and modeling; Transfer learning; Graphical models, EM and Bayesian learning; Classification and clustering; Vector quantization and self-organizing maps; Recurrent networks and dynamical systems; Time series forecasting; Single- and zero-shot learning; Ensemble learning; Feature selection; Graphs and networks: Nonlinear dimensionality reduction; manifold learning; Statistical and mathematical aspects of learning; Trustworthy AI; Image processing; Data mining; Machine learning for signal processing; Multimodal interfaces and multichannel processing; Vision and sensory systems; Data visualization; Identification of non-linear dynamical systems; Machine learning for healthcare; Evolutionary computation for machine learning; Bioinformatics; Bio-inspired systems; Brain-computer interfaces Papers will be presented orally (single track) and in poster sessions; all posters will be complemented by a short oral presentation during a plenary session. The selection of papers will differentiate between oral and posters presentations according to the topics, and not to the level of quality.
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