statistiche ricercatore

Continente	#
EU - Europa	9.017
NA - Nord America	908
AS - Asia	895
SA - Sud America	119
AF - Africa	45
OC - Oceania	29
Continente sconosciuto - Info sul continente non disponibili	1
Totale	11.014

Nazione	#
IT - Italia	8.681
US - Stati Uniti d'America	863
SG - Singapore	258
CN - Cina	248
BR - Brasile	92
DE - Germania	87
VN - Vietnam	78
HK - Hong Kong	74
SE - Svezia	59
GB - Regno Unito	42
FR - Francia	39
IN - India	33
KR - Corea	32
CA - Canada	31
BD - Bangladesh	29
FI - Finlandia	26
JP - Giappone	25
AU - Australia	23
ID - Indonesia	13
ES - Italia	12
AT - Austria	11
MY - Malesia	11
NL - Olanda	11
ZA - Sudafrica	11
IQ - Iraq	10
MX - Messico	10
AR - Argentina	9
IR - Iran	9
PK - Pakistan	9
TW - Taiwan	9
CI - Costa d'Avorio	8
PT - Portogallo	8
TR - Turchia	8
NG - Nigeria	7
PH - Filippine	7
PL - Polonia	7
RU - Federazione Russa	7
TH - Thailandia	7
UA - Ucraina	7
DZ - Algeria	6
GR - Grecia	6
IL - Israele	6
NZ - Nuova Zelanda	6
CH - Svizzera	5
EC - Ecuador	5
AZ - Azerbaigian	4
CO - Colombia	4
SA - Arabia Saudita	4
AM - Armenia	3
MA - Marocco	3
NP - Nepal	3
VE - Venezuela	3
AE - Emirati Arabi Uniti	2
CL - Cile	2
CR - Costa Rica	2
EG - Egitto	2
IE - Irlanda	2
JO - Giordania	2
KW - Kuwait	2
NO - Norvegia	2
PE - Perù	2
TN - Tunisia	2
UY - Uruguay	2
UZ - Uzbekistan	2
YE - Yemen	2
AO - Angola	1
BA - Bosnia-Erzegovina	1
BE - Belgio	1
BW - Botswana	1
ET - Etiopia	1
EU - Europa	1
GT - Guatemala	1
IM - Isola di Man	1
KE - Kenya	1
KZ - Kazakistan	1
LB - Libano	1
LT - Lituania	1
LY - Libia	1
MO - Macao, regione amministrativa speciale della Cina	1
NI - Nicaragua	1
OM - Oman	1
PS - Palestinian Territory	1
RO - Romania	1
SN - Senegal	1
Totale	11.014

Nome	#
Deep neural rejection against adversarial examples	2.206
IntelliAV: Toward the feasibility of building intelligent anti-malware on Android devices	2.048
AI Security and Safety: The PRALab Research Experience	1.027
Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving	740
FADER: Fast Adversarial Example Rejection	712
ImageNet-Patch: a dataset for benchmarking machine learning robustness against adversarial patches	706
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers	643
secml: Secure and explainable machine learning in Python	642
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples	561
Explainability-based Debugging of Machine Learning for Vulnerability Discovery	531
Evaluating Adversarial Robustness of Detection-based Defenses against Adversarial Examples	482
An Experimental Analysis of Semi-supervised Learning for Malware Detection	277
Understanding Regression in Continual Learning for Malware Detection	260
Data drift in Android malware detection	99
Evaluating line-level localization ability of learning-based code vulnerability detection models	86
Robust image classification with multi-modal large language models	81
Totale	11.101

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2020/2021	47	0	0	0	0	0	0	0	0	0	0	0	47
2021/2022	350	33	14	6	19	24	36	26	9	45	50	39	49
2022/2023	977	36	92	76	50	79	117	78	75	87	83	131	73
2023/2024	2.095	57	43	69	226	274	291	329	186	77	151	217	175
2024/2025	3.736	879	937	397	421	204	270	301	50	52	47	92	86
2025/2026	2.005	180	158	159	114	154	99	319	165	216	215	131	95
Totale													11.101

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