K5IR825D - Adaptive autonomous robotic behaviour
UE24 - MIR - K5IR841D - Deep-sea vehicles and missions for ocean sciences (H. Hugel)
The objective of this lecture is to provide insight specific to deep-sea underwater vehicles and their operation. It gives an overview of existing underwater vehicles, observatories and operations procedures, with emphasis on the Underwater Systems developed and operated within the French Oceanographic Fleet. Sensors and equipment required for deep water submarine operations will be presented. A focus on acoustic communication necessary for the operation of AUVs (Autonomous Underwater Vehicles) will be carried out in terms of principle, strategies and equipment. Instrumental architecture and key principles of distributed multi-sensor acquisition systems will be exposed. Visual perception in deep-sea operations as well as 3D representation of natural structures on the ocean floor will also be deepened
K5IR824D - Data-driven Machine Perception (R.P. Maxer Pinon)
This module aims at equipping students with the ability of creating machine learning (and deep learning) models for usual intelligent robotic perception tasks. Computer vision and machine listening on a marine environment are the two target fields of application of the contents of this course, however other modalities (e.g. hyperspectral imaging, natural language,...) will be discussed. After the module students will be capable at identifying perception tasks to which deep learning techniques can be applied. Students will be able to build specific models to solve these problems and assess their performance. They will also know the main specificities of image and audio for marine applications.
Marine Mechatronics (V. Hugel)
Participants will carry out tutorial and practical work on marine and underwater robotsunder the supervision of lecturers. Matlab/Simulink and Ubuntu/ROS will be used to take over the following robotic platforms :• Marius sailing robot• 8-thruster BlueROV underwater robot• 3-thruster fully equipped CORAL underwater robot
K5IR743D - Reinforcement Learning (R. Maxer)
This course presents the main framework of reinforcement learning (RL). At the end of the course, the student will be able to identify and frame problems under this formalism. He will master the vocabulary associated with the RL field, and will be aware of the main obstacles to tackle when using and developing RL approaches (e.g. exploitation-exploration trade-off, sample efficiency). Moreover students will be capable of understanding and implementing “vanilla” algorithms of the core methods in RL (e.g. Q-learning and policy optimisation) and analyze/apply some specific advanced algorithms (e.g. A2C and PPO).
MIR students feedback - Retour des étudiants MIR
Module servant à recueillir tous les commentaires des étudiants du MIR, depuis les évaluations des matières jusqu'aux choix des options d'études.
K5IR742D - Deep Learning (R. Marxer Pau)
After this course the students will be able to identify the deep learning (DL) approaches to be applied to multiple types of machine learning problems, depending on the task and the data inputs/outputs. Students will know how to build and train advanced DL models with the use of existing publicly available software tools. We will also introduce the main shortcomings and limitations of deep learning techniques such as the problem of interpretation and the exploitation of adversarial attacks.
K5IR722D - Underwater Acoustics (M. Saillard)
Objectives:The aim of this course is to give the students understanding of both Physics of acoustic waves and signal processing techniques, in order to be able to suggest which system is appropriate for given specifications, to predict its performances through simple models, to implement data processing algorithms and to interpret the results. The complementarity of deep learning techniques with physics based approach is highlighted.Contents:- Propagation of acoustic waves in shallow and deep water, scattering, Doppler effect.- Signal processing : positioning, detection and ranging, noise correlation, time reversal.
K5IR714D - Programming Language Level-Up (S. Baroudi)
K5IR711D - Scientific Writing Skills (A. Ventard)
K5IR741D - MIR - Machine Learning (A.Paiement @ S. Paris)
K5IR733D - Control theory of multivariable linear systems (N. Boizot)
ECUE 4.1 spécialité football Staps Toulon (P. Desfontaine)
- Culture foot
- théorie de l'APSA
- Approche technicotactique
- Préparation physique intégrée
- Littérature Foot
Fonctionnement général L2 & L3 APAS
BNSSA (E. Watelain)
Information pour BNSSA et secourisme dans le cadre du Certificat de Spécialisation Sauvetage et Secours en Milieu Aquatique.
Journée de la femme sportive
ECUE 2.1.3 Liaison Théorie Pratique Basket Ball (S Vitiello)
Spécialité sportive - Liaison Théorie Pratique - Triathlon - (Arnaud Belz)
Vous trouverez ici les différents supports de cours
S3S1T09A SPE NATATION L1-L2 et L3 (I. Plasseraud)
Semestre 1
Évaluation L3, statuts particuliers inclus
L'évaluation est réalisée à l'oral sur dossier devant les autres étudiants du même groupe.
10mn d'oral suivi de 10 mn de questionnements.
SAE 221 SAE PPP (Compétence 4) (JM. Vallier)
ECUE 1.3.2 Théorie APSA Transversale Rugby (X. Pujos)
ECUE 1.3.1 Spécialité Rugby Théorie et Articles (X. Pujos)
UE 14 - L1 STAPS - Compétences informationnelles (BU)
RA 1.2.1 - Histoire 1 (G. Lassalle)
Le cours d'histoire en STAPS commence par une introduction aux Sciences Humaines et Sociales (SHS), expliquant leurs origines, représentations, et les disciplines de la sociologie, psychologie, et histoire.
Il aborde ensuite l'histoire des STAPS, les perceptions et problématiques de l'histoire, et les nouvelles conceptions de cette discipline. Le programme couvre l'évolution du sport, depuis l'Antiquité grecque et romaine, en passant par le Moyen Âge et la Renaissance, jusqu'à la naissance des sports modernes et la relance des Jeux Olympiques.
Chaque période met en lumière les pratiques physiques, les valeurs culturelles et les transformations sociales associées au sport.
ECUE 2.5.5 Élaboration d'un projet professionnel (K. Saidi)
Ce cours de TD avaient pour objectifs de mieux comprendre comment construire de manière méthodique un projet professionnel allant de la phase de préparation (bilan de compétences, identification de métier cible…) jusqu’à la rédaction du projet.
ECUE 2.3.1 - Physiologie 2 (O. Saidi)
L'organisme requiert un apport continu en protéines, glucides, lipides, vitamines et sels pour sa croissance, son entretien et son métabolisme. Ces éléments se trouvent dans les aliments à des proportions directement absorbables très faibles, nécessitant ainsi une transformation avant leur utilisation.
La digestion englobe l'ensemble des processus d'ingestion et de transformation dans le tractus gastro-intestinal, l’absorption des nutriments ainsi que l'élimination des résidus solides et liquides non absorbés. Elle implique de nombreux processus mécaniques et chimiques étroitement interconnectés et parfaitement synchronisés, régulés à la fois par le système nerveux et hormonal.
ECUE 1.2 Cours théorique polyvalence rugby ( B. Dagneaux)
L2 EM - UE34 (RA344) Course d'orientation en Education & Motricité ( J.BOUSQUET)
Contenu relatif aux TD de polyvalence L1 course d'orientation
ECUE 1.1.2 Socio Histoire Rugby (X. Pujos)
Socio Histoire Rugby
- Noyau Central règlement et Esprit du jeu
- Notion de matrices d'action et forme sèche
- matrice offensive
ECUE 1.1.2 Cours Théorie Spé Rugby (X. Pujos)
Cours Théorie Spé Rugby L1 :
- Le Monde du Rugby : Socio Histoire de l'antiquité à nos jours
- Le Noyau Central du Règlement et l'esprit du jeu qui en découle
- Présentation de la notion de matrice en sport collectif et forme sèche de la matrice offensive
ECUE 2.5.4 Découverte des Parcours Professionnels
UE2.1 Spécialité Sportive : Liaison Théorie-Pratique Athlétisme (G. Lassalle)
UE 11 RA 1.1.2 Neurophysiologie (L. Coudrat & O. Caron)
- Previous page
- 1(current)
- 2(current)
- 3(current)
- 4(current)
- 5(current)
- 6(current)
- 7(current)
- 8(current)
- 9(current)
- 10(current)
- 11(current)
- 12(current)
- 13(current)
- 14(current)
- 15(current)
- 16(current)
- 17(current)
- 18(current)
- 19(current)
- 20(current)
- 21(current)
- 22(current)
- 23(current)
- 24(current)
- 25(current)
- 26(current)
- 27(current)
- 28(current)
- 29(current)
- 30(current)
- 31(current)
- 32(current)
- 33(current)
- 34(current)
- 35(current)
- 36(current)
- 37(current)
- 38(current)
- 39(current)
- 40(current)
- 41(current)
- 42(current)
- 43(current)
- 44(current)
- 45(current)
- 46(current)
- 47(current)
- 48(current)
- 49(current)
- 50(current)
- 51(current)
- 52(current)
- 53(current)
- 54(current)
- 55(current)
- 56(current)
- 57(current)
- 58(current)
- 59(current)
- 60(current)
- 61(current)
- 62(current)
- 63(current)
- 64
- 65(current)
- 66(current)
- 67(current)
- 68(current)
- 69(current)
- 70(current)
- 71(current)
- 72(current)
- 73(current)
- 74(current)
- 75(current)
- 76(current)
- 77(current)
- 78(current)
- 79(current)
- 80(current)
- 81(current)
- 82(current)
- 83(current)
- 84(current)
- 85(current)
- 86(current)
- 87(current)
- 88(current)
- 89(current)
- 90(current)
- 91(current)
- 92(current)
- 93(current)
- 94(current)
- 95(current)
- 96(current)
- 97(current)
- 98(current)
- 99(current)
- 100(current)
- 101(current)
- 102(current)
- 103(current)
- 104(current)
- 105(current)
- 106(current)
- 107(current)
- 108(current)
- 109(current)
- 110(current)
- 111(current)
- 112(current)
- 113(current)
- 114(current)
- 115(current)
- 116(current)
- 117(current)
- 118(current)
- 119(current)
- 120(current)
- 121(current)
- 122(current)
- 123(current)
- 124(current)
- 125(current)
- Next page